Jiazi Tian
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View article: A Hybrid Enumeration Framework for Optimal Counterfactual Generation in Post-Acute COVID-19 Heart Failure
A Hybrid Enumeration Framework for Optimal Counterfactual Generation in Post-Acute COVID-19 Heart Failure Open
Counterfactual inference provides a mathematical framework for reasoning about hypothetical outcomes under alternative interventions, bridging causal reasoning and predictive modeling. We present a counterfactual inference framework for in…
View article: Quantifying Diagnostic Signal Decay in Dementia: A National Study of Medicare Hospitalization Data
Quantifying Diagnostic Signal Decay in Dementia: A National Study of Medicare Hospitalization Data Open
Background: Artificial intelligence (AI) models in healthcare depend on the fidelity of diagnostic data, yet the quality of such data is often compromised by variability in clinical documentation practices. In dementia, a condition already…
View article: Temporal Learning with Dynamic Range (TLDR) for Modeling Recurrent Exposure and Treatment Outcomes
Temporal Learning with Dynamic Range (TLDR) for Modeling Recurrent Exposure and Treatment Outcomes Open
Background The temporal sequence of clinical events is crucial in outcomes research, yet standard machine learning (ML) approaches often overlook this aspect in electronic health records (EHRs), limiting predictive accuracy. Methods We int…
View article: An Agentic AI Workflow for Detecting Cognitive Concerns in Real-world Data
An Agentic AI Workflow for Detecting Cognitive Concerns in Real-world Data Open
Early identification of cognitive concerns is critical but often hindered by subtle symptom presentation. This study developed and validated a fully automated, multi-agent AI workflow using LLaMA 3 8B to identify cognitive concerns in 3,33…
View article: Precision phenotyping for curating research cohorts of patients with unexplained post-acute sequelae of COVID-19
Precision phenotyping for curating research cohorts of patients with unexplained post-acute sequelae of COVID-19 Open
This research was funded by the US National Institute of Allergy and Infectious Diseases (NIAID).
View article: Temporal Characterization and Visualization of Revolving Therapy-Events in Lung Cancer Patients
Temporal Characterization and Visualization of Revolving Therapy-Events in Lung Cancer Patients Open
This paper presents a comprehensive workflow for integrating revolving events into the transitive sequential pattern mining (tSPM+) algorithm and Machine Learning for Health Outcomes (MLHO) framework, emphasizing best practices and pitfall…
View article: Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion
Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion Open
Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the P…